Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Active power generator 2, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit [W] is highly overall correlated with HourCounters Average GridOn Avg. [h]High correlation
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 1 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°]High correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W]High correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average GridOn Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with Active power limit [W] and 1 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Active Power Gen 2 Avg. [W] is highly overall correlated with HourCounters Average Gen2 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (62.3%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (56.1%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (58.1%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (58.3%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (72.9%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (77.2%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (79.0%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (78.5%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (50.7%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (76.4%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (77.5%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (63.5%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (71.4%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (73.3%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (72.2%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (68.8%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (57.0%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (67.4%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (53.2%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (60.8%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.5%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (86.3%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (92.5%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (71.4%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (82.9%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (85.5%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (62.7%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (52.5%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (79.7%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (75.7%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (94.9%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.6%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.8%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (92.0%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (80.1%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (78.2%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (79.0%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (73.2%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (74.9%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (70.4%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (75.9%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (63.1%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (82.7%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (78.3%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (78.9%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.8%) Imbalance
Active power limit [W] is highly imbalanced (98.3%) Imbalance
Active power limit source is highly imbalanced (99.8%) Imbalance
Power factor set point is highly imbalanced (99.8%) Imbalance
Power factor set point source is highly imbalanced (99.8%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (90.5%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (65.7%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (73.4%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (52.5%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (71.3%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (70.5%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (59.1%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (57.0%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (57.5%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (76.8%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (78.7%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (78.8%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.3%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (99.1%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (97.8%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (94.9%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (81.6%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (67.7%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.3%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (96.5%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (70.4%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (94.9%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (75.5%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (83.9%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (77.1%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (80.3%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (72.7%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (61.1%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (63.2%) Imbalance
Total Active power [W] is highly imbalanced (99.8%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (96.4%) Imbalance
Total reactive power [var] is highly imbalanced (95.5%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-14 17:43:54.001498
Analysis finished2025-05-14 17:44:23.130946
Duration29.13 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-14T19:44:23.171371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T19:44:23.254180image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24297 
1
 
1911

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Length

2025-05-14T19:44:23.328643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.364663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24297
92.7%
1 1911
 
7.3%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23831 
1
 
2377

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Length

2025-05-14T19:44:23.551141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.587424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23983 
1
 
2225

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Length

2025-05-14T19:44:23.632241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.668618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23983
91.5%
1 2225
 
8.5%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23997 
1
 
2211

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Length

2025-05-14T19:44:23.712580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.750281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23997
91.6%
1 2211
 
8.4%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24990 
1
 
1218

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Length

2025-05-14T19:44:23.794715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.830251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24990
95.4%
1 1218
 
4.6%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25242 
1
 
966

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Length

2025-05-14T19:44:23.873889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.909484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25339 
1
 
869

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Length

2025-05-14T19:44:23.951607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:23.988854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25339
96.7%
1 869
 
3.3%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25310 
1
 
898

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%

Length

2025-05-14T19:44:24.031375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.066987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25310
96.6%
1 898
 
3.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23388 
1
2820 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%

Length

2025-05-14T19:44:24.110710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.147133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%

Most occurring characters

ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23388
89.2%
1 2820
 
10.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25194 
1
 
1014

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%

Length

2025-05-14T19:44:24.192559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.228129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25194
96.1%
1 1014
 
3.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21883 
1
4325 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Length

2025-05-14T19:44:24.270262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.308249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Most occurring characters

ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21883
83.5%
1 4325
 
16.5%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25258 
1
 
950

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Length

2025-05-14T19:44:24.353271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.389077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25258
96.4%
1 950
 
3.6%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:24.433103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.466481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:24.505785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.541012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24382 
1
 
1826

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Length

2025-05-14T19:44:24.580385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.616448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring characters

ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24899 
1
 
1309

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%

Length

2025-05-14T19:44:24.660558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.696714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24899
95.0%
1 1309
 
5.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:24.739205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.774085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25015 
1
 
1193

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%

Length

2025-05-14T19:44:24.813586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.849358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25015
95.4%
1 1193
 
4.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24948 
1
 
1260

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%

Length

2025-05-14T19:44:24.893261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:24.929121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24948
95.2%
1 1260
 
4.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24739 
1
 
1469

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%

Length

2025-05-14T19:44:24.971403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.009099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24739
94.4%
1 1469
 
5.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23901 
1
 
2307

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Length

2025-05-14T19:44:25.051785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.088307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24642 
1
 
1566

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%

Length

2025-05-14T19:44:25.134290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.170039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%

Most occurring characters

ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24642
94.0%
1 1566
 
6.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23191 
1
3017 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Length

2025-05-14T19:44:25.212199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.250612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23191
88.5%
1 3017
 
11.5%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23593 
1
2615 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Length

2025-05-14T19:44:25.295175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.331972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23593
90.0%
1 2615
 
10.0%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23185 
1
3023 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Length

2025-05-14T19:44:25.379423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.416441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24184 
1
 
2024

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Length

2025-05-14T19:44:25.461400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.498757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24184
92.3%
1 2024
 
7.7%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23176 
1
3032 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Length

2025-05-14T19:44:25.541401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.578303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Most occurring characters

ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23176
88.4%
1 3032
 
11.6%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25888 
1
 
320

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Length

2025-05-14T19:44:25.625105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.661242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25888
98.8%
1 320
 
1.2%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25706 
1
 
502

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Length

2025-05-14T19:44:25.704059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.741520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25706
98.1%
1 502
 
1.9%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25967 
1
 
241

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Length

2025-05-14T19:44:25.783829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.819985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24900 
1
 
1308

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Length

2025-05-14T19:44:25.864095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.900255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24900
95.0%
1 1308
 
5.0%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25541 
1
 
667

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Length

2025-05-14T19:44:25.943115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:25.980777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25541
97.5%
1 667
 
2.5%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25668 
1
 
540

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%

Length

2025-05-14T19:44:26.024786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.061337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%

Most occurring characters

ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25668
97.9%
1 540
 
2.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22337 
1
3871 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%

Length

2025-05-14T19:44:26.105443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.141938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%

Most occurring characters

ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22337
85.2%
1 3871
 
14.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:26.186314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.221233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24323 
1
 
1885

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%

Length

2025-05-14T19:44:26.399465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.435317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24323
92.8%
1 1885
 
7.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23540 
1
2668 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%

Length

2025-05-14T19:44:26.479064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.515336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%

Most occurring characters

ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23540
89.8%
1 2668
 
10.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22729 
1
3479 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%

Length

2025-05-14T19:44:26.559659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.597913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%

Most occurring characters

ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22729
86.7%
1 3479
 
13.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22744 
1
3464 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Length

2025-05-14T19:44:26.642553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.679170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Most occurring characters

ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22744
86.8%
1 3464
 
13.2%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25377 
1
 
831

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Length

2025-05-14T19:44:26.725664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.761635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25377
96.8%
1 831
 
3.2%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25156 
1
 
1052

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%

Length

2025-05-14T19:44:26.803698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.841124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25156
96.0%
1 1052
 
4.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26057 
1
 
151

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Length

2025-05-14T19:44:26.883409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.919060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25971 
1
 
237

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Length

2025-05-14T19:44:26.963025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:26.999080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25941 
1
 
267

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Length

2025-05-14T19:44:27.042920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.078858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25941
99.0%
1 267
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25951 
1
 
257

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Length

2025-05-14T19:44:27.121440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.158966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25951
99.0%
1 257
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25395 
1
 
813

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Length

2025-05-14T19:44:27.201036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.236611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25297 
1
 
911

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Length

2025-05-14T19:44:27.280516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.316234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25297
96.5%
1 911
 
3.5%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25337 
1
 
871

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Length

2025-05-14T19:44:27.360309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.398509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25009 
1
 
1199

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Length

2025-05-14T19:44:27.440965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.476741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25009
95.4%
1 1199
 
4.6%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25109 
1
 
1099

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Length

2025-05-14T19:44:27.520786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.556624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25109
95.8%
1 1099
 
4.2%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24835 
1
 
1373

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Length

2025-05-14T19:44:27.599452image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.637251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25169 
1
 
1039

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Length

2025-05-14T19:44:27.679877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.716546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25169
96.0%
1 1039
 
4.0%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24355 
1
 
1853

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Length

2025-05-14T19:44:27.761181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.797018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24355
92.9%
1 1853
 
7.1%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22637 
1
3571 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%

Length

2025-05-14T19:44:27.839237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.877287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%

Most occurring characters

ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22637
86.4%
1 3571
 
13.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23098 
1
3110 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%

Length

2025-05-14T19:44:27.921722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:27.958179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23098
88.1%
1 3110
 
11.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21634 
1
4574 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Length

2025-05-14T19:44:28.004434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.041328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Most occurring characters

ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21634
82.5%
1 4574
 
17.5%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25533 
1
 
675

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Length

2025-05-14T19:44:28.086006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.123477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25300 
1
 
908

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Length

2025-05-14T19:44:28.165841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.201276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25300
96.5%
1 908
 
3.5%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25335 
1
 
873

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Length

2025-05-14T19:44:28.245191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.280968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25384 
1
 
824

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Length

2025-05-14T19:44:28.323110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.361202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.404109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.437649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.478609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.511830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.550995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.586205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.625822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.659365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.700787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.734511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.773943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.809008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.848489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.882056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:28.923205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:28.956692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26167 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Length

2025-05-14T19:44:28.996416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.034034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-14T19:44:29.217540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.253218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:29.296971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.330352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-14T19:44:29.369926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.407628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-14T19:44:29.449814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.485365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25890 
1
 
318

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Length

2025-05-14T19:44:29.528939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.564530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25890
98.8%
1 318
 
1.2%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24533 
1
 
1675

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Length

2025-05-14T19:44:29.606981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.644626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24533
93.6%
1 1675
 
6.4%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25020 
1
 
1188

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Length

2025-05-14T19:44:29.687130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.723440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23538 
1
2670 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%

Length

2025-05-14T19:44:29.768911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.806561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%

Most occurring characters

ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23538
89.8%
1 2670
 
10.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24894 
1
 
1314

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%

Length

2025-05-14T19:44:29.852657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.888337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24894
95.0%
1 1314
 
5.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22455 
1
3753 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Length

2025-05-14T19:44:29.930640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:29.968909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Most occurring characters

ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22455
85.7%
1 3753
 
14.3%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24845 
1
 
1363

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Length

2025-05-14T19:44:30.013468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.049234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24845
94.8%
1 1363
 
5.2%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:30.093480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.127072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24064 
1
 
2144

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Length

2025-05-14T19:44:30.166610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.204955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23901 
1
 
2307

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Length

2025-05-14T19:44:30.249964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.286631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23901
91.2%
1 2307
 
8.8%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23940 
1
 
2268

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Length

2025-05-14T19:44:30.332577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.369106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23173 
1
3035 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

Length

2025-05-14T19:44:30.414633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.452855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

Most occurring characters

ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23173
88.4%
1 3035
 
11.6%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25220 
1
 
988

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Length

2025-05-14T19:44:30.497341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.533138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25323 
1
 
885

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

Length

2025-05-14T19:44:30.577295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.613611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25323
96.6%
1 885
 
3.4%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25326 
1
 
882

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Length

2025-05-14T19:44:30.656087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.693996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23117 
1
3091 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%

Length

2025-05-14T19:44:30.737459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.774279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23117
88.2%
1 3091
 
11.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:30.820544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.854429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26193 
1
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Length

2025-05-14T19:44:30.893771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:30.931596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26189 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Length

2025-05-14T19:44:30.974279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.010312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26151 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Length

2025-05-14T19:44:31.054950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.091111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26057 
1
 
151

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Length

2025-05-14T19:44:31.133971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.171513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26057
99.4%
1 151
 
0.6%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25474 
1
 
734

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

Length

2025-05-14T19:44:31.214311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.250389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25474
97.2%
1 734
 
2.8%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24668 
1
 
1540

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Length

2025-05-14T19:44:31.294665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.330585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring characters

ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22850 
1
3358 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

Length

2025-05-14T19:44:31.373202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.412115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

Most occurring characters

ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22850
87.2%
1 3358
 
12.8%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26193 
1
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Length

2025-05-14T19:44:31.456837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.492794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26112 
1
 
96

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%

Length

2025-05-14T19:44:31.536816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.572772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26112
99.6%
1 96
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24841 
1
 
1367

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Length

2025-05-14T19:44:31.616498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.654337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26056 
1
 
152

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Length

2025-05-14T19:44:31.697237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.733776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:31.778181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.811796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:31.851396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.886623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:31.926457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:31.960186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.001674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.181676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.220882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.254249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.295046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.328314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.369501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.404750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.444757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.480016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.519098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.552372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.593486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.627097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:32.666817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.703185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25144 
1
 
1064

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Length

2025-05-14T19:44:32.744163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.780522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25144
95.9%
1 1064
 
4.1%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25592 
1
 
616

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Length

2025-05-14T19:44:32.824732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.860782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25592
97.6%
1 616
 
2.4%

Production LatestAverage Active Power Gen 2 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25234 
1
 
974

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Length

2025-05-14T19:44:32.902990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:32.940504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25234
96.3%
1 974
 
3.7%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25407 
1
 
801

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Length

2025-05-14T19:44:32.983238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.019339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25407
96.9%
1 801
 
3.1%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24981 
1
 
1227

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Length

2025-05-14T19:44:33.063753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.099812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24981
95.3%
1 1227
 
4.7%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24207 
1
 
2001

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Length

2025-05-14T19:44:33.142349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.179938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24207
92.4%
1 2001
 
7.6%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24359 
1
 
1849

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%

Length

2025-05-14T19:44:33.222361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.258424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24359
92.9%
1 1849
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22901 
1
3307 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%

Length

2025-05-14T19:44:33.304261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.341218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%

Most occurring characters

ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22901
87.4%
1 3307
 
12.6%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:33.385576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.422229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:33.462219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.495689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:33.537420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.570945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26205 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Length

2025-05-14T19:44:33.610671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.648210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26110 
1
 
98

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%

Length

2025-05-14T19:44:33.691001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.727413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26110
99.6%
1 98
 
0.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:33.772182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.805933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:44:33.845330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.880307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26080 
1
 
128

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Length

2025-05-14T19:44:33.919945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:44:33.955678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Correlations

2025-05-14T19:44:34.081669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power limit [W]1.0000.2730.0000.0000.0000.0000.0000.0330.0020.0000.0150.0020.0230.0350.0000.0100.0030.0000.0130.0000.0000.0010.0050.0000.0000.0090.0020.0000.0120.0000.0000.0000.0000.0200.0000.0090.0070.0040.0000.0230.0110.0090.0160.0000.0060.0150.0160.0110.0170.0250.0000.0070.0000.0050.0050.0090.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.1180.1650.0050.0000.2680.5040.0670.2610.0500.0490.0000.0000.0000.2730.2730.0230.0080.0000.0100.0000.0000.0170.0000.0000.0000.0130.0110.0160.0130.0000.000
Active power limit source0.2731.0000.0000.0000.0050.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0010.0180.0000.0220.0000.0000.0000.0180.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0600.0240.0000.0000.0570.4520.0180.3230.0320.0310.0000.0000.0000.8750.8750.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0100.0000.0000.0170.0000.000
Ambient Temp. Avg. [°C]0.0000.0001.0000.0110.0000.0050.0030.0100.0000.0120.0180.0170.0120.0110.0340.0190.0050.0570.0180.0110.0140.0080.0360.0410.0120.0000.0140.0200.0280.0000.0120.0000.0190.0180.0250.0000.0200.0070.0000.0060.0120.0130.0090.0000.0070.0000.0000.0090.0070.0000.0100.0050.0180.0000.0000.0000.0000.0000.0000.0000.0230.0270.0000.0340.0290.0310.0000.0000.0190.0210.0000.0000.0000.0000.0070.0080.0050.0000.1030.0000.0000.0210.0090.0060.0180.0000.0050.0090.0070.0000.0170.0080.0170.0070.0420.0000.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0111.0000.0930.0290.0260.0000.0110.0020.0060.0120.0000.0000.0080.0140.0110.0020.0000.0000.0000.0010.0060.0000.0070.0260.0000.0050.0000.0000.0070.0000.0140.0370.0060.0160.0130.0000.0000.0220.0150.0160.0150.0000.0130.0000.0090.0000.0150.0090.0000.0000.0260.0220.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0260.0000.0110.0000.0000.0250.0030.0070.0210.0050.0080.0090.0140.0000.0200.0290.0000.0150.0000.0000.000
Ambient WindDir Relative Avg. [°]0.0000.0050.0000.0931.0000.0150.0220.0000.0080.0700.0960.0450.0330.0000.0230.0000.0100.0000.0000.0000.0110.0000.0150.0230.0000.0670.0010.0000.0050.0140.0160.0000.0630.0900.0430.0480.0040.0000.0000.0460.0040.0000.0000.0000.0100.0000.0000.0000.0070.0000.0000.0000.0730.0290.0230.0160.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0330.0440.0000.0580.0000.0000.0370.0000.0000.0000.0110.0000.0130.0050.0050.0750.0000.0050.0920.0000.0240.0060.0490.0000.0640.0730.0330.0350.0130.0000.013
Ambient WindSpeed Avg. [m/s]0.0000.0000.0050.0290.0151.0000.1370.0840.0120.1000.0240.0690.0470.0000.0270.0000.0200.0080.0110.0860.0500.0560.0590.0540.0380.0000.0000.0060.0000.0170.0270.0150.1130.0810.0800.0490.0040.0000.0320.0250.2190.2100.2260.0000.2500.0960.0810.0480.2320.0830.0840.0510.0360.0290.0330.0310.0030.0000.0000.0220.0110.0200.0060.0000.0100.0000.0000.0000.0400.0510.0000.0000.0000.0000.0000.0410.0050.0000.0120.0000.0000.0270.0920.1190.0340.0000.0000.2140.0270.0000.1160.0640.0680.0340.0000.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0030.0260.0220.1371.0000.0280.0520.0710.0480.0690.0420.0100.0030.0000.0000.0050.0020.0370.0210.0330.0400.0350.0340.0000.0000.0000.0040.0150.0200.0090.0450.0750.0280.0290.0050.0080.0300.0310.1170.1180.1200.0000.1170.1260.0550.0840.1060.1110.0450.0740.0410.0380.0320.0350.0000.0000.0000.0180.0120.0070.0190.0140.0000.0090.0010.0000.0260.0460.0000.0000.0000.0000.0000.0560.0140.0000.0000.0000.0000.0300.0570.0540.0300.0070.0130.0980.0280.0000.0420.0590.0240.0070.0000.0000.000
Ambient WindSpeed Min. [m/s]0.0330.0000.0100.0000.0000.0840.0281.0000.0310.0940.0230.1250.0870.0000.0230.0000.0190.0070.0030.0300.0250.0270.0550.0250.0280.0130.0000.0000.0000.0060.0000.0160.0820.0360.1100.0630.0130.0000.0270.0410.0700.0820.0740.0000.0760.0220.1100.0310.0800.0350.1120.0350.0820.0740.0730.0580.0000.0000.0000.0120.0080.0140.0000.0000.0030.0060.0070.0160.0700.0760.0320.0490.0000.0250.0000.0550.0000.0000.0000.0000.0000.0460.0470.0730.0500.0260.0530.0740.0620.0000.0720.0360.1000.0500.0050.0000.000
Ambient WindSpeed StdDev [m/s]0.0020.0000.0000.0110.0080.0120.0520.0311.0000.0590.0000.0590.1040.0120.0030.0000.0000.0090.0020.0260.0210.0100.0000.0120.0000.0000.0200.0100.0080.0200.0210.0070.0270.0300.0150.0810.0170.0000.0190.0210.0240.0210.0300.0070.0200.0240.0480.1410.0300.0390.0340.1360.0290.0380.0410.0250.0000.0000.0000.0260.0000.0100.0200.0000.0000.0000.0000.0000.0000.0160.0000.0110.0000.0110.0080.0150.0560.0000.0300.0000.0000.0240.0000.0250.0140.0000.0350.0350.0020.0080.0230.0130.0020.0690.0000.0000.008
Blades PitchAngle Avg. [°]0.0000.0000.0120.0020.0700.1000.0710.0940.0591.0000.2360.4250.4340.0150.0360.0000.0290.0140.0090.0210.0480.0150.0780.1160.0250.0510.0200.0210.0160.0060.0120.0020.2110.1990.1880.1970.0300.0130.0420.2330.1610.1630.1860.0000.2080.1900.2150.2320.1920.1810.1650.2600.3970.2640.2010.2320.0000.0000.0020.0320.0200.0350.0090.0200.0220.0330.1760.1310.1810.3640.0130.0030.1870.0110.1030.0790.0740.0000.0160.0000.0000.3120.1110.2390.3010.1210.2380.2000.2910.0260.2270.1760.1530.1540.0000.0000.019
Blades PitchAngle Max. [°]0.0150.0110.0180.0060.0960.0240.0480.0230.0000.2361.0000.1040.0750.0030.0000.0060.0180.0000.0040.0170.0150.0100.0600.0400.0260.0840.0100.0110.0000.0100.0000.0050.0880.2300.0420.0590.0150.0000.0060.1950.1020.0980.1160.0000.1390.1500.1260.1630.1180.1410.0800.1200.1450.1330.0430.0550.0000.0090.0050.0000.0000.0140.0000.0070.0120.0190.1080.0980.0140.1640.0000.0230.1140.0000.0440.1570.0380.0000.0250.0110.0110.1980.0000.1080.2130.0000.0540.1240.1230.0000.0900.2050.0410.0610.0070.0000.000
Blades PitchAngle Min. [°]0.0020.0000.0170.0120.0450.0690.0690.1250.0590.4250.1041.0000.5400.0000.0240.0030.0100.0000.0000.0320.0490.0270.0720.0910.0210.0190.0180.0220.0000.0000.0000.0000.1970.1280.2950.2260.0310.0070.0200.3020.1310.1250.1480.0000.1710.1350.1740.1720.1770.1290.1570.2280.6220.4160.3230.3840.0000.0000.0000.0100.0130.0110.0030.0180.0130.0230.1560.1100.3080.4940.0140.0000.1680.0040.0890.0950.0440.0040.0110.0000.0000.3900.1670.2930.3530.2270.4330.1860.4470.0460.2050.1060.2480.1790.0060.0000.040
Blades PitchAngle StdDev [°]0.0230.0000.0120.0000.0330.0470.0420.0870.1040.4340.0750.5401.0000.0000.0220.0000.0170.0040.0060.0080.0310.0020.0390.0740.0000.0350.0160.0300.0060.0060.0000.0000.1580.1300.1980.3740.0330.0210.0240.2570.1030.0960.1210.0000.1700.1420.2470.2230.1400.1230.1840.2650.4660.3270.2350.3800.0000.0000.0020.0140.0140.0210.0190.0220.0190.0310.1460.1110.2400.3710.0410.0280.1430.0280.0810.0530.0910.0030.0160.0000.0000.2690.1320.2410.2630.1870.4550.1440.3310.0700.1630.1100.1560.2930.0050.0000.061
Controller Ground Temp. Avg. [°C]0.0350.0000.0110.0000.0000.0000.0100.0000.0120.0150.0030.0000.0001.0000.0000.0220.0000.0000.0100.0070.0000.0000.0020.0080.0040.0000.0030.0110.0020.0150.0070.0000.0100.0000.0080.0000.0000.0170.0000.0040.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0030.0120.0000.0030.0080.0000.0000.0000.0000.0000.0000.0000.0000.0130.0120.0040.0180.0140.0170.0550.0630.0000.0000.0120.0070.0000.0000.0000.0000.0000.0050.0120.0000.0090.0000.0000.0000.0000.0000.0100.0060.0000.0040.0050.0000.000
Controller Hub Temp. Avg. [°C]0.0000.0000.0340.0080.0230.0270.0030.0230.0030.0360.0000.0240.0220.0001.0000.0200.0000.0080.0170.0000.0000.0030.0000.0000.0000.0130.0160.0220.0100.0020.0000.0140.0140.0320.0230.0300.0000.0230.0080.0250.0490.0500.0580.0000.0400.0160.0270.0290.0390.0280.0340.0270.0300.0060.0050.0190.0040.0050.0090.0050.0070.0030.0000.0360.0290.0250.0370.0490.0550.0520.0170.0130.0350.0130.0000.0050.0060.0000.0150.0000.0000.0300.0270.0480.0290.0060.0220.0470.0060.0000.0180.0240.0130.0210.0650.0000.000
Controller Top Temp. Avg. [°C]0.0100.0000.0190.0140.0000.0000.0000.0000.0000.0000.0060.0030.0000.0220.0201.0000.0050.0350.0120.0000.0000.0000.0000.0000.0130.0180.0280.0220.0190.0000.0000.0000.0000.0000.0090.0130.0080.0100.0000.0060.0000.0000.0000.0000.0040.0000.0040.0050.0000.0000.0000.0000.0000.0070.0160.0000.0000.0000.0020.0000.0100.0060.0090.0510.0230.0160.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0530.0000.0000.0000.0040.0000.0000.0130.0090.0000.0000.0000.0000.0000.0150.0060.0110.0000.022
Controller VCP ChokecoilTemp. Avg. [°C]0.0030.0000.0050.0110.0100.0200.0000.0190.0000.0290.0180.0100.0170.0000.0000.0051.0000.0350.0240.0390.0440.0110.0110.0310.0220.0180.0150.0100.0240.0550.0580.0640.0160.0000.0000.0220.0350.0000.0280.0250.0060.0050.0050.0030.0000.0070.0110.0000.0000.0190.0110.0060.0000.0160.0120.0000.0000.0000.0000.0120.0310.0230.0170.0640.0340.0290.0070.0000.0350.0090.0080.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0230.0240.0100.0250.0080.0070.0080.0110.0030.0180.0090.0000.0360.0070.0000.008
Controller VCP Temp. Avg. [°C]0.0000.0000.0570.0020.0000.0080.0050.0070.0090.0140.0000.0000.0040.0000.0080.0350.0351.0000.0130.0110.0100.0080.0360.0350.0120.0130.0460.0280.0270.0230.0310.0170.0110.0000.0140.0190.0600.0360.0000.0140.0070.0000.0040.0000.0000.0030.0000.0000.0050.0080.0000.0000.0100.0080.0060.0100.0000.0000.0070.0000.0070.0190.0170.0420.0270.0240.0100.0090.0000.0080.0030.0000.0100.0000.0010.0110.0190.0050.0840.0000.0000.0080.0000.0070.0130.0000.0110.0040.0080.0000.0090.0040.0150.0190.0320.0000.000
Controller VCP WaterTemp. Avg. [°C]0.0130.0000.0180.0000.0000.0110.0020.0030.0020.0090.0040.0000.0060.0100.0170.0120.0240.0131.0000.0420.0270.0300.0250.0170.0410.0000.0540.0350.2860.0580.0560.0530.0350.0000.0140.0260.0060.0210.1430.0120.0150.0170.0200.0000.0130.0010.0000.0000.0210.0050.0000.0050.0030.0000.0190.0000.0070.0000.0050.2140.2950.2720.0070.0210.0230.0240.0000.0090.0000.0040.0000.0040.0000.0000.0000.0300.0090.0000.0340.0000.0000.0180.0070.0090.0150.0190.0060.0240.0030.0050.0230.0100.0300.0000.0000.0000.004
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0110.0000.0000.0860.0370.0300.0260.0210.0170.0320.0080.0070.0000.0000.0390.0110.0421.0000.2660.2400.1750.0920.2120.0080.0460.0200.0290.0880.0910.1170.0910.0460.0620.0540.0270.0000.0780.0310.0740.0740.0850.0000.0790.0660.0450.0280.0810.0650.0360.0270.0100.0280.0300.0190.0000.0000.0000.0530.0440.0440.0090.0060.0050.0000.0280.0380.0000.0130.0000.0000.0280.0000.0000.0330.0000.0200.0160.0000.0000.0410.0580.0010.0360.0050.0050.0840.0180.0020.0790.0470.0750.0580.0040.0000.003
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0140.0000.0110.0500.0210.0250.0210.0480.0150.0490.0310.0000.0000.0000.0440.0100.0270.2661.0000.1240.2290.1500.2530.0170.0320.0340.0430.1040.0960.1100.1300.0620.0960.0680.0340.0010.0520.0690.0510.0550.0550.0000.0560.0560.0440.0330.0540.0590.0250.0290.0520.0470.0480.0210.0020.0000.0000.0420.0450.0460.0040.0000.0060.0020.0390.0520.0000.0600.0000.0000.0370.0000.0000.0300.0070.0130.0160.0000.0000.1000.0400.0000.0910.0020.0220.0590.0390.0180.1240.0520.1040.0780.0200.0000.014
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0010.0000.0080.0010.0000.0560.0330.0270.0100.0150.0100.0270.0020.0000.0030.0000.0110.0080.0300.2400.1241.0000.1950.0720.2630.0350.0550.0100.0300.0570.0390.0560.1270.0380.0760.0850.0280.0000.0430.0000.0580.0610.0630.0090.0570.0680.0330.0250.0610.0720.0360.0300.0060.0190.0110.0200.0070.0000.0000.0410.0400.0310.0000.0040.0080.0000.0470.0300.0260.0000.0000.0000.0470.0000.0140.0000.0030.0150.0000.0000.0000.0290.0400.0120.0310.0370.0230.0620.0320.0000.1210.0640.0810.0820.0000.0000.006
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0050.0000.0360.0060.0150.0590.0400.0550.0000.0780.0600.0720.0390.0020.0000.0000.0110.0360.0250.1750.2290.1951.0000.2110.2110.0410.0410.0230.0280.0640.0650.0740.1640.0540.1410.0800.0530.0000.0350.0730.0660.0620.0740.0000.0740.0740.0640.0440.0770.0740.0350.0420.0710.0530.0550.0620.0010.0040.0000.0300.0370.0530.0080.0090.0000.0000.0470.0470.0250.0860.0000.0000.0470.0000.0090.0040.0000.0340.0100.0000.0000.1070.0750.0050.1050.0000.0220.0830.0630.0070.1540.0640.1290.0840.0140.0000.000
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0000.0410.0000.0230.0540.0350.0250.0120.1160.0400.0910.0740.0080.0000.0000.0310.0350.0170.0920.1500.0720.2111.0000.1400.0470.0430.0300.0180.0610.0670.0550.1760.0960.1390.0820.0440.0140.0250.0570.0360.0290.0350.0000.0320.0480.0410.0400.0350.0430.0180.0470.0880.0650.0750.0460.0000.0000.0000.0240.0310.0320.0050.0040.0000.0020.0660.0470.0540.0920.0000.0000.0660.0000.0330.0220.0130.0120.0140.0000.0000.1130.0380.0150.1100.0070.0190.0420.0620.0110.1810.0940.1220.0740.0180.0000.000
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0120.0070.0000.0380.0340.0280.0000.0250.0260.0210.0000.0040.0000.0130.0220.0120.0410.2120.2530.2630.2110.1401.0000.0380.0690.0160.0430.0890.0720.1190.1410.0640.0570.0620.0250.0000.0310.0150.0290.0290.0330.0000.0390.0530.0140.0180.0370.0390.0000.0100.0000.0240.0150.0050.0000.0100.0000.0380.0460.0570.0090.0000.0070.0000.0410.0340.0000.0000.0000.0000.0390.0000.0050.0040.0050.0270.0240.0000.0000.0330.0240.0000.0310.0160.0060.0430.0220.0000.1230.0800.0840.0670.0080.0000.000
Gear Oil TemperatureLevel1 Avg. [°C]0.0090.0000.0000.0260.0670.0000.0000.0130.0000.0510.0840.0190.0350.0000.0130.0180.0180.0130.0000.0080.0170.0350.0410.0470.0381.0000.0050.0220.0000.0140.0130.0120.0680.0930.0370.0750.0040.0050.0130.0420.0190.0160.0260.0000.0220.0300.0410.0250.0230.0380.0380.0360.0330.0140.0150.0310.0000.0040.0000.0160.0000.0060.0150.0000.0080.0120.0760.0450.0000.0340.0000.0000.0760.0000.0510.0000.0210.0370.0390.0000.0000.0710.0080.0100.0710.0080.0460.0310.0200.0000.0750.0870.0160.0890.0220.0000.000
Generator Bearing Temp. Avg. [°C]0.0020.0000.0140.0000.0010.0000.0000.0000.0200.0200.0100.0180.0160.0030.0160.0280.0150.0460.0540.0460.0320.0550.0410.0430.0690.0051.0000.0490.0380.0430.0530.0540.0550.0320.0120.0390.0320.0170.0050.0050.0000.0070.0030.0000.0000.0070.0000.0130.0130.0100.0100.0250.0060.0170.0140.0080.0000.0000.0000.0280.0400.0320.0080.0480.0310.0140.0140.0000.0050.0130.0000.0000.0140.0000.0180.0000.0110.0210.0140.0000.0000.0160.0000.0160.0160.0000.0060.0150.0080.0000.0410.0440.0180.0380.0000.0000.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0200.0050.0000.0060.0000.0000.0100.0210.0110.0220.0300.0110.0220.0220.0100.0280.0350.0200.0340.0100.0230.0300.0160.0220.0491.0000.0280.0200.0250.0280.0270.0300.0300.0290.0190.0420.0050.0180.0350.0410.0380.0000.0350.0080.0170.0150.0390.0130.0250.0220.0220.0000.0180.0320.0050.0040.0030.0120.0140.0170.0200.0270.0130.0360.0130.0000.0160.0230.0000.0000.0100.0000.0130.0120.0000.0000.0210.0000.0000.0230.0110.0310.0250.0000.0180.0390.0080.0000.0250.0220.0190.0330.0000.0000.000
Generator CoolingWater Temp. Avg. [°C]0.0120.0000.0280.0000.0050.0000.0040.0000.0080.0160.0000.0000.0060.0020.0100.0190.0240.0270.2860.0290.0430.0300.0280.0180.0430.0000.0380.0281.0000.0620.0540.0550.0190.0190.0040.0140.0190.0250.1010.0100.0000.0000.0000.0000.0160.0150.0130.0130.0110.0000.0110.0080.0000.0060.0100.0050.0100.0000.0050.1790.2370.2140.0080.0310.0170.0180.0010.0150.0110.0000.0000.0060.0000.0000.0000.0190.0000.0000.0430.0000.0000.0080.0180.0130.0170.0170.0060.0110.0000.0130.0200.0190.0160.0000.0160.0000.011
Generator Phase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0140.0170.0150.0060.0200.0060.0100.0000.0060.0150.0020.0000.0550.0230.0580.0880.1040.0570.0640.0610.0890.0140.0430.0200.0621.0000.3590.3110.0280.0100.0000.0170.0080.0110.0510.0120.0260.0290.0300.0050.0060.0000.0000.0150.0170.0230.0090.0110.0000.0220.0280.0110.0110.0210.0170.0810.0780.0680.0140.0380.0290.0250.0000.0000.0080.0000.0000.0000.0000.0000.0000.0150.0090.0000.0060.0000.0000.0100.0020.0130.0140.0290.0150.0180.0130.0030.0260.0060.0250.0160.0060.0000.007
Generator Phase2 Temp. Avg. [°C]0.0000.0000.0120.0070.0160.0270.0200.0000.0210.0120.0000.0000.0000.0070.0000.0000.0580.0310.0560.0910.0960.0390.0650.0670.0720.0130.0530.0250.0540.3591.0000.2370.0250.0120.0120.0140.0120.0000.0530.0160.0220.0380.0260.0030.0070.0000.0000.0080.0220.0110.0020.0080.0080.0280.0130.0170.0000.0220.0180.0820.0900.0720.0170.0320.0290.0240.0000.0000.0130.0000.0000.0000.0000.0000.0000.0110.0000.0050.0260.0000.0000.0150.0000.0020.0220.0280.0120.0190.0080.0000.0210.0000.0380.0080.0000.0000.006
Generator Phase3 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0150.0090.0160.0070.0020.0050.0000.0000.0000.0140.0000.0640.0170.0530.1170.1100.0560.0740.0550.1190.0120.0540.0280.0550.3110.2371.0000.0240.0140.0120.0120.0050.0150.0410.0120.0220.0290.0330.0000.0140.0000.0000.0210.0270.0150.0000.0160.0000.0080.0140.0210.0040.0000.0000.0780.0640.0610.0180.0540.0370.0260.0000.0000.0120.0070.0020.0000.0000.0000.0000.0140.0160.0000.0170.0000.0000.0120.0000.0000.0140.0300.0170.0220.0150.0020.0330.0000.0380.0030.0000.0000.000
Generator RPM Avg. [RPM]0.0000.0000.0190.0140.0630.1130.0450.0820.0270.2110.0880.1970.1580.0100.0140.0000.0160.0110.0350.0910.1300.1270.1640.1760.1410.0680.0550.0270.0190.0280.0250.0241.0000.3540.3810.4630.0300.0000.0070.1620.1530.1520.1560.0060.1490.1360.1460.1550.1500.1300.1150.1660.1970.1260.1300.1070.0000.0000.0000.0250.0310.0320.0000.0070.0000.0090.1670.1280.0760.2090.0070.0000.1780.0030.0900.0160.0350.0050.0210.0000.0000.2670.0530.0960.2740.0250.1050.1530.1580.0560.7280.3310.3410.3990.0160.0000.050
Generator RPM Max. [RPM]0.0200.0130.0180.0370.0900.0810.0750.0360.0300.1990.2300.1280.1300.0000.0320.0000.0000.0000.0000.0460.0620.0380.0540.0960.0640.0930.0320.0300.0190.0100.0120.0140.3541.0000.1300.2640.0200.0050.0240.1310.1300.1290.1360.0000.1340.1730.1380.1700.1270.1780.0970.1380.1680.1320.0740.0720.0000.0000.0000.0370.0250.0310.0230.0000.0000.0000.1010.1080.0890.1960.0220.0260.1090.0130.0320.0320.0320.0000.0310.0130.0130.1780.0160.1610.2060.0000.1180.1290.1250.0170.3000.7300.1060.2030.0280.0000.011
Generator RPM Min. [RPM]0.0000.0000.0250.0060.0430.0800.0280.1100.0150.1880.0420.2950.1980.0080.0230.0090.0000.0140.0140.0620.0960.0760.1410.1390.0570.0370.0120.0300.0040.0000.0120.0120.3810.1301.0000.2690.0350.0000.0210.1950.1170.1190.1200.0000.1180.0670.1620.0650.1470.0570.1710.0990.2560.1700.1960.1490.0160.0060.0000.0110.0210.0250.0120.0060.0000.0050.1310.0780.1670.3120.0000.0000.1360.0010.0750.1020.0250.0090.0000.0000.0000.3260.1400.1310.2850.0240.1980.1590.1820.0690.3710.1180.7550.2210.0140.0000.055
Generator RPM StdDev [RPM]0.0090.0000.0000.0160.0480.0490.0290.0630.0810.1970.0590.2260.3740.0000.0300.0130.0220.0190.0260.0540.0680.0850.0800.0820.0620.0750.0390.0290.0140.0170.0140.0120.4630.2640.2691.0000.0300.0120.0210.2430.1270.1290.1360.0000.1550.1460.2470.2190.1480.1550.2050.2550.1880.1260.1260.2200.0000.0000.0080.0340.0330.0250.0140.0110.0000.0000.1460.1010.0340.1980.0350.0030.1450.0240.0870.0390.0920.0000.0310.0000.0000.2490.0250.1390.2530.0160.2790.1520.1270.0840.4240.2400.2270.6690.0130.0000.056
Generator SlipRing Temp. Avg. [°C]0.0070.0000.0200.0130.0040.0040.0050.0130.0170.0300.0150.0310.0330.0000.0000.0080.0350.0600.0060.0270.0340.0280.0530.0440.0250.0040.0320.0190.0190.0080.0120.0050.0300.0200.0350.0301.0000.0180.0150.0070.0000.0000.0000.0050.0120.0000.0190.0200.0020.0000.0190.0000.0090.0170.0200.0120.0020.0100.0110.0180.0270.0230.1100.0000.0000.0210.0000.0000.0160.0270.0000.0000.0000.0000.0000.0000.0140.0130.0430.0000.0000.0070.0240.0140.0110.0110.0170.0000.0000.0000.0290.0230.0250.0170.0000.0000.000
Grid Busbar Temp. Avg. [°C]0.0040.0000.0070.0000.0000.0000.0080.0000.0000.0130.0000.0070.0210.0170.0230.0100.0000.0360.0210.0000.0010.0000.0000.0140.0000.0050.0170.0420.0250.0110.0000.0150.0000.0050.0000.0120.0181.0000.0070.0080.0080.0080.0000.0000.0260.0160.0150.0160.0130.0120.0070.0110.0010.0000.0000.0180.0000.0000.0000.0080.0070.0170.0230.0460.0250.0200.0000.0000.0100.0130.0000.0000.0000.0000.0000.0000.0060.0270.0300.0000.0000.0030.0170.0220.0000.0170.0180.0150.0160.0000.0050.0000.0020.0100.0000.0000.007
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0320.0300.0270.0190.0420.0060.0200.0240.0000.0080.0000.0280.0000.1430.0780.0520.0430.0350.0250.0310.0130.0050.0050.1010.0510.0530.0410.0070.0240.0210.0210.0150.0071.0000.0200.0800.0830.0840.0000.0750.0510.0520.0430.0750.0710.0430.0510.0160.0180.0270.0090.0060.0000.0070.1930.1860.1570.0060.0050.0070.0000.0260.0430.0000.0090.0010.0000.0260.0000.0000.0310.0070.0120.0080.0000.0000.0290.0130.0390.0270.0060.0000.0720.0000.0000.0050.0170.0180.0100.0000.0000.000
Grid Production CosPhi Avg.0.0230.0000.0060.0220.0460.0250.0310.0410.0210.2330.1950.3020.2570.0040.0250.0060.0250.0140.0120.0310.0690.0000.0730.0570.0150.0420.0050.0180.0100.0120.0160.0120.1620.1310.1950.2430.0070.0080.0201.0000.1520.1580.1940.0000.1990.1820.2210.1960.2090.2170.1750.2040.3810.2510.1960.2420.0000.0010.0000.0250.0070.0240.0100.0000.0000.0000.0960.0950.0000.4350.0000.0000.0960.0000.0340.1370.0630.0080.0260.0000.0000.5230.0000.1940.4960.0440.3500.2090.2670.0430.1650.1010.1470.1950.0260.0000.093
Grid Production CurrentPhase1 Avg. [A]0.0110.0000.0120.0150.0040.2190.1170.0700.0240.1610.1020.1310.1030.0000.0490.0000.0060.0070.0150.0740.0510.0580.0660.0360.0290.0190.0000.0350.0000.0260.0220.0220.1530.1300.1170.1270.0000.0080.0800.1521.0000.7900.7420.0010.5610.2450.2640.2410.6540.3070.3030.2790.2030.1090.1080.1070.0000.0000.0000.0540.0410.0310.0350.0000.0000.0060.1820.2060.0900.1460.0230.0000.2000.0180.0360.1600.0530.0000.0210.0000.0000.2490.2200.3300.2530.0100.0640.6300.1440.0070.1570.1040.0930.1090.0180.0000.009
Grid Production CurrentPhase2 Avg. [A]0.0090.0000.0130.0160.0000.2100.1180.0820.0210.1630.0980.1250.0960.0000.0500.0000.0050.0000.0170.0740.0550.0610.0620.0290.0290.0160.0070.0410.0000.0290.0380.0290.1520.1290.1190.1290.0000.0080.0830.1580.7901.0000.7530.0000.5390.2360.2550.2310.6260.3080.3090.2820.2290.1200.1250.1140.0000.0000.0000.0580.0420.0360.0490.0000.0050.0000.1730.1940.0830.1410.0210.0000.1910.0160.0380.1550.0580.0000.0360.0000.0000.2310.2050.3270.2770.0000.0610.6010.1550.0080.1520.1010.0960.1110.0260.0000.010
Grid Production CurrentPhase3 Avg. [A]0.0160.0010.0090.0150.0000.2260.1200.0740.0300.1860.1160.1480.1210.0000.0580.0000.0050.0040.0200.0850.0550.0630.0740.0350.0330.0260.0030.0380.0000.0300.0260.0330.1560.1360.1200.1360.0000.0000.0840.1940.7420.7531.0000.0030.6020.2800.2950.2640.6870.3540.3280.3150.2350.1310.1210.1210.0080.0000.0000.0540.0400.0290.0430.0150.0040.0000.1780.2020.0860.1780.0130.0060.1930.0170.0300.1410.0640.0000.0320.0010.0010.2550.2040.3670.2890.0040.0810.6480.1650.0000.1650.1090.0950.1170.0280.0000.010
Grid Production Frequency Avg. [Hz]0.0000.0180.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0050.0030.0000.0060.0000.0000.0000.0050.0000.0000.0000.0010.0000.0031.0000.0000.0000.0000.0000.0020.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0060.0000.0040.0060.0000.0060.0000.0110.0000.0000.0020.0180.0180.0000.0000.0060.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0060.0000.0070.0130.0100.2500.1170.0760.0200.2080.1390.1710.1700.0050.0400.0040.0000.0000.0130.0790.0560.0570.0740.0320.0390.0220.0000.0350.0160.0060.0070.0140.1490.1340.1180.1550.0120.0260.0750.1990.5610.5390.6020.0001.0000.3430.4050.3630.6940.3220.3050.3350.1390.1210.0570.1150.0020.0000.0000.0300.0350.0240.0000.0000.0000.0000.1220.1550.0810.2160.0000.0000.1290.0000.0000.1530.0490.0000.0260.0000.0000.1760.2820.4260.1570.0220.1230.6660.0950.0000.1560.1070.0950.1460.0120.0000.007
Grid Production PossiblePower Max. [W]0.0150.0220.0000.0000.0000.0960.1260.0220.0240.1900.1500.1350.1420.0000.0160.0000.0070.0030.0010.0660.0560.0680.0740.0480.0530.0300.0070.0080.0150.0000.0000.0000.1360.1730.0670.1460.0000.0160.0510.1820.2450.2360.2800.0000.3431.0000.2790.3560.2880.7010.2100.2900.1420.1230.0370.1300.0000.0000.0000.0070.0040.0000.0000.0120.0000.0030.1380.1520.0580.1830.0020.0060.1330.0160.0150.0490.0360.0360.0160.0220.0220.1540.0960.2360.1590.0410.1100.2950.1230.0000.1400.1400.0600.1550.0330.0000.006
Grid Production PossiblePower Min. [W]0.0160.0000.0000.0090.0000.0810.0550.1100.0480.2150.1260.1740.2470.0000.0270.0040.0110.0000.0000.0450.0440.0330.0640.0410.0140.0410.0000.0170.0130.0000.0000.0000.1460.1380.1620.2470.0190.0150.0520.2210.2640.2550.2950.0000.4050.2791.0000.2900.3180.2730.5680.2980.1440.1090.0550.1740.0000.0000.0000.0180.0130.0190.0040.0190.0140.0090.0850.1060.0760.2300.0030.0060.0990.0000.0040.0850.0730.0000.0310.0000.0000.1730.1180.2830.1680.0050.2410.3280.0920.0210.1450.1170.1360.2090.0190.0000.021
Grid Production PossiblePower StdDev [W]0.0110.0000.0090.0000.0000.0480.0840.0310.1410.2320.1630.1720.2230.0000.0290.0050.0000.0000.0000.0280.0330.0250.0440.0400.0180.0250.0130.0150.0130.0150.0080.0210.1550.1700.0650.2190.0200.0160.0430.1960.2410.2310.2640.0000.3630.3560.2901.0000.2870.3060.2190.7260.2020.1750.0680.1360.0000.0000.0000.0200.0200.0000.0000.0140.0080.0050.1230.1390.0840.2320.0140.0000.1200.0170.0160.0660.0870.0000.0130.0000.0000.1720.1200.2610.1880.0740.1410.2890.1650.0000.1380.1450.0530.1800.0000.0000.009
Grid Production Power Avg. [W]0.0170.0000.0070.0150.0070.2320.1060.0800.0300.1920.1180.1770.1400.0000.0390.0000.0000.0050.0210.0810.0540.0610.0770.0350.0370.0230.0130.0390.0110.0170.0220.0270.1500.1270.1470.1480.0020.0130.0750.2090.6540.6260.6870.0020.6940.2880.3180.2871.0000.3460.3370.3420.1920.1180.1100.1230.0070.0000.0000.0480.0350.0310.0230.0100.0000.0000.1740.2000.0850.1910.0230.0070.1920.0170.0310.1570.0640.0090.0270.0000.0000.2990.2800.4470.2360.0140.1110.8550.1380.0000.1570.0990.1180.1360.0200.0050.009
Grid Production Power Max. [W]0.0250.0180.0000.0090.0000.0830.1110.0350.0390.1810.1410.1290.1230.0000.0280.0000.0190.0080.0050.0650.0590.0720.0740.0430.0390.0380.0100.0130.0000.0230.0110.0150.1300.1780.0570.1550.0000.0120.0710.2170.3070.3080.3540.0000.3220.7010.2730.3060.3461.0000.2240.3290.1720.1500.0480.1230.0000.0100.0000.0340.0240.0260.0130.0090.0000.0000.1120.1180.0380.1960.0000.0280.1150.0010.0140.0620.0310.0270.0240.0180.0180.1900.0860.2550.2270.0070.0960.3400.1390.0000.1330.1420.0430.1520.0400.0000.000
Grid Production Power Min. [W]0.0000.0000.0100.0000.0000.0840.0450.1120.0340.1650.0800.1570.1840.0000.0340.0000.0110.0000.0000.0360.0250.0360.0350.0180.0000.0380.0100.0250.0110.0090.0020.0000.1150.0970.1710.2050.0190.0070.0430.1750.3030.3090.3280.0070.3050.2100.5680.2190.3370.2241.0000.2550.1480.0880.1160.1450.0000.0010.0000.0290.0230.0190.0130.0100.0090.0120.0880.0860.0580.1580.0400.0140.1010.0300.0370.0860.0990.0000.0280.0000.0000.1740.0990.2640.1700.0000.2050.3470.0970.0000.1110.0770.1390.1670.0190.0000.000
Grid Production Power StdDev [W]0.0070.0000.0050.0000.0000.0510.0740.0350.1360.2600.1200.2280.2650.0030.0270.0000.0060.0000.0050.0270.0290.0300.0420.0470.0100.0360.0250.0220.0080.0110.0080.0160.1660.1380.0990.2550.0000.0110.0510.2040.2790.2820.3150.0000.3350.2900.2980.7260.3420.3290.2551.0000.2590.1890.1090.1890.0000.0000.0000.0150.0220.0060.0080.0100.0050.0140.2150.1640.1500.2450.0270.0000.2230.0230.1230.0770.0870.0000.0110.0000.0000.2440.1450.2740.2330.1230.1610.3380.1980.0000.1530.1170.0780.2120.0000.0000.000
Grid Production ReactivePower Avg. [W]0.0000.0000.0180.0260.0730.0360.0410.0820.0290.3970.1450.6220.4660.0120.0300.0000.0000.0100.0030.0100.0520.0060.0710.0880.0000.0330.0060.0220.0000.0000.0080.0000.1970.1680.2560.1880.0090.0010.0160.3810.2030.2290.2350.0000.1390.1420.1440.2020.1920.1720.1480.2591.0000.5540.4100.4750.0000.0000.0000.0170.0090.0200.0170.0130.0210.0210.1860.1370.3440.6000.0100.0140.1800.0060.0940.0850.0620.0000.0250.0000.0000.5600.1720.2610.6540.2450.5150.1820.6830.0500.2040.1310.1990.1490.0200.0000.067
Grid Production ReactivePower Max. [W]0.0050.0060.0000.0220.0290.0290.0380.0740.0380.2640.1330.4160.3270.0000.0060.0070.0160.0080.0000.0280.0470.0190.0530.0650.0240.0140.0170.0000.0060.0220.0280.0080.1260.1320.1700.1260.0170.0000.0180.2510.1090.1200.1310.0000.1210.1230.1090.1750.1180.1500.0880.1890.5541.0000.3490.3450.0000.0000.0000.0120.0150.0210.0170.0010.0040.0080.1110.0780.2330.3960.0100.0200.1070.0150.0610.0830.1580.0000.0130.0060.0060.3250.1200.1990.3420.2330.3130.1110.4460.0090.1250.1050.1390.0920.0000.0000.027
Grid Production ReactivePower Min. [W]0.0050.0000.0000.0260.0230.0330.0320.0730.0410.2010.0430.3230.2350.0030.0050.0160.0120.0060.0190.0300.0480.0110.0550.0750.0150.0150.0140.0180.0100.0280.0130.0140.1300.0740.1960.1260.0200.0000.0270.1960.1080.1250.1210.0000.0570.0370.0550.0680.1100.0480.1160.1090.4100.3491.0000.2710.0000.0000.0000.0260.0090.0270.0050.0160.0030.0140.1260.0900.1720.2830.0180.0220.1250.0000.0780.0600.1830.0000.0080.0000.0000.3150.0830.1070.3150.0970.2580.1030.2960.0420.1360.0560.1720.0910.0110.0000.029
Grid Production ReactivePower StdDev [W]0.0090.0000.0000.0000.0160.0310.0350.0580.0250.2320.0550.3840.3800.0080.0190.0000.0000.0100.0000.0190.0210.0200.0620.0460.0050.0310.0080.0320.0050.0110.0170.0210.1070.0720.1490.2200.0120.0180.0090.2420.1070.1140.1210.0000.1150.1300.1740.1360.1230.1230.1450.1890.4750.3450.2711.0000.0000.0000.0050.0050.0000.0040.0000.0120.0090.0260.1060.0830.2710.3960.0300.0200.1040.0100.0570.0070.0960.0350.0000.0000.0000.2930.1780.1890.2910.2040.4220.1170.3780.0450.1010.0720.1000.1920.0020.0000.068
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0070.0000.0020.0070.0010.0000.0000.0000.0000.0050.0100.0110.0000.0040.0000.0000.0160.0000.0020.0000.0060.0000.0000.0000.0080.0000.0020.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0001.0000.5780.5860.0000.0140.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0060.0000.0000.0020.0000.0000.0130.0150.0000.0030.0000.0000.0060.0000.0000.0000.0070.0080.0000.0000.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0040.0000.0100.0040.0000.0040.0000.0210.0220.0000.0000.0000.0060.0000.0100.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0010.0000.0000.0000.0000.0000.5781.0000.5820.0000.0000.0000.0000.0000.0040.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0150.0050.0000.0040.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0050.0000.0020.0000.0090.0020.0000.0070.0050.0000.0000.0000.0000.0000.0000.0000.0000.0030.0050.0170.0180.0000.0000.0000.0000.0080.0110.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.5860.5821.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0310.0060.0000.0000.0000.0000.0000.0000.0000.0090.0130.0000.0000.0100.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0220.0180.0120.0260.0320.0000.0100.0140.0000.0050.0000.0120.0000.2140.0530.0420.0410.0300.0240.0380.0160.0280.0120.1790.0810.0820.0780.0250.0370.0110.0340.0180.0080.1930.0250.0540.0580.0540.0000.0300.0070.0180.0200.0480.0340.0290.0150.0170.0120.0260.0050.0000.0000.0001.0000.3700.3040.0230.0150.0060.0180.0190.0320.0000.0010.0040.0000.0210.0000.0000.0340.0110.0000.0160.0000.0000.0300.0050.0140.0340.0280.0090.0440.0000.0040.0160.0200.0290.0120.0080.0000.005
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0230.0000.0050.0110.0120.0080.0000.0200.0000.0130.0140.0000.0070.0100.0310.0070.2950.0440.0450.0400.0370.0310.0460.0000.0400.0140.2370.0780.0900.0640.0310.0250.0210.0330.0270.0070.1860.0070.0410.0420.0400.0000.0350.0040.0130.0200.0350.0240.0230.0220.0090.0150.0090.0000.0140.0000.0090.3701.0000.2290.0160.0220.0230.0350.0000.0110.0060.0200.0000.0000.0000.0000.0040.0360.0160.0060.0270.0000.0000.0240.0190.0120.0260.0230.0180.0360.0000.0000.0240.0280.0350.0160.0000.0000.004
Grid RotorInvPhase3 Temp. Avg. [°C]0.0090.0000.0270.0000.0000.0200.0070.0140.0100.0350.0140.0110.0210.0000.0030.0060.0230.0190.2720.0440.0460.0310.0530.0320.0570.0060.0320.0170.2140.0680.0720.0610.0320.0310.0250.0250.0230.0170.1570.0240.0310.0360.0290.0000.0240.0000.0190.0000.0310.0260.0190.0060.0200.0210.0270.0040.0000.0000.0000.3040.2291.0000.0070.0140.0020.0000.0070.0090.0000.0230.0000.0030.0080.0030.0000.0150.0090.0000.0250.0000.0000.0310.0110.0050.0340.0280.0170.0330.0000.0020.0270.0340.0300.0190.0000.0000.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0060.0190.0000.0200.0090.0000.0030.0190.0000.0000.0090.0170.0170.0070.0090.0040.0000.0080.0050.0090.0150.0080.0200.0080.0140.0170.0180.0000.0230.0120.0140.1100.0230.0060.0100.0350.0490.0430.0000.0000.0000.0040.0000.0230.0130.0130.0080.0170.0170.0050.0000.0000.0000.0000.0230.0160.0071.0000.0000.0000.0130.0170.0000.0050.0030.0220.0060.0170.0120.0240.0150.0130.0130.0320.0000.0000.0120.0090.0070.0220.0100.0000.0200.0000.0000.0100.0120.0070.0000.0000.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0340.0000.0000.0000.0140.0000.0000.0200.0070.0180.0220.0000.0360.0510.0640.0420.0210.0060.0000.0040.0090.0040.0000.0000.0480.0270.0310.0380.0320.0540.0070.0000.0060.0110.0000.0460.0050.0000.0000.0000.0150.0000.0000.0120.0190.0140.0100.0090.0100.0100.0130.0010.0160.0120.0000.0000.0000.0150.0220.0140.0001.0000.1710.2070.0000.0070.0300.0250.0120.0000.0000.0050.0030.0040.0140.0000.0350.0000.0000.0020.0420.0050.0000.0080.0220.0120.0000.0000.0040.0000.0000.0000.0070.0000.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0290.0190.0000.0100.0000.0030.0000.0220.0120.0130.0190.0130.0290.0230.0340.0270.0230.0050.0060.0080.0000.0000.0070.0080.0310.0130.0170.0290.0290.0370.0000.0000.0000.0000.0000.0250.0070.0000.0000.0050.0040.0030.0000.0000.0140.0080.0000.0000.0090.0050.0210.0040.0030.0090.0000.0040.0000.0060.0230.0020.0000.1711.0000.2200.0020.0140.0360.0240.0000.0000.0030.0000.0020.0160.0220.0100.0310.0000.0000.0000.0510.0000.0000.0070.0220.0100.0000.0090.0000.0000.0000.0000.0090.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0310.0000.0000.0000.0090.0060.0000.0330.0190.0230.0310.0120.0250.0160.0290.0240.0240.0000.0020.0000.0000.0020.0000.0120.0140.0360.0180.0250.0240.0260.0090.0000.0050.0000.0210.0200.0000.0000.0060.0000.0000.0000.0000.0030.0090.0050.0000.0000.0120.0140.0210.0080.0140.0260.0000.0000.0000.0180.0350.0000.0130.2070.2201.0000.0020.0140.0650.0380.0030.0000.0030.0060.0000.0000.0100.0000.0330.0000.0000.0000.0730.0000.0000.0000.0310.0000.0120.0000.0080.0000.0000.0000.0010.0000.000
HourCounters Average AlarmActive Avg. [h]0.1180.0600.0000.0000.0330.0000.0010.0070.0000.1760.1080.1560.1460.0040.0370.0000.0070.0100.0000.0280.0390.0470.0470.0660.0410.0760.0140.0130.0010.0000.0000.0000.1670.1010.1310.1460.0000.0000.0260.0960.1820.1730.1780.0000.1220.1380.0850.1230.1740.1120.0880.2150.1860.1110.1260.1060.0000.0000.0000.0190.0000.0070.0170.0000.0020.0021.0000.6900.2690.0240.1570.1350.9340.1980.5300.1070.0310.0260.0000.0600.0600.2660.1790.0000.2360.1280.0000.1860.1380.0000.1730.0890.1080.1180.0230.0000.000
HourCounters Average AmbientOk Avg. [h]0.1650.0240.0000.0000.0440.0000.0000.0160.0000.1310.0980.1100.1110.0180.0490.0000.0000.0090.0090.0380.0520.0300.0470.0470.0340.0450.0000.0000.0150.0000.0000.0000.1280.1080.0780.1010.0000.0000.0430.0950.2060.1940.2020.0000.1550.1520.1060.1390.2000.1180.0860.1640.1370.0780.0900.0830.0000.0000.0000.0320.0110.0090.0000.0070.0140.0140.6901.0000.2020.0200.4090.2230.7090.2760.1260.1400.0220.0230.0000.0240.0240.2070.2090.0000.1700.0980.0000.2070.1010.0000.1350.0880.0660.0780.0290.0000.000
HourCounters Average Gen1 Avg. [h]0.0050.0000.0190.0000.0000.0400.0260.0700.0000.1810.0140.3080.2400.0140.0550.0000.0350.0000.0000.0000.0000.0260.0250.0540.0000.0000.0050.0160.0110.0080.0130.0120.0760.0890.1670.0340.0160.0100.0000.0000.0900.0830.0860.0060.0810.0580.0760.0840.0850.0380.0580.1500.3440.2330.1720.2710.0130.0100.0310.0000.0060.0000.0050.0300.0360.0650.2690.2021.0000.5480.0060.0000.2700.0080.1330.0120.0100.0060.0130.0000.0000.0670.5940.3360.0580.2650.1870.0890.2550.0000.0890.0690.1420.0160.0000.0000.008
HourCounters Average Gen2 Avg. [h]0.0000.0000.0210.0280.0580.0510.0460.0760.0160.3640.1640.4940.3710.0170.0520.0040.0090.0080.0040.0130.0600.0000.0860.0920.0000.0340.0130.0230.0000.0000.0000.0070.2090.1960.3120.1980.0270.0130.0090.4350.1460.1410.1780.0000.2160.1830.2300.2320.1910.1960.1580.2450.6000.3960.2830.3960.0000.0000.0060.0010.0200.0230.0030.0250.0240.0380.0240.0200.5481.0000.0130.0000.0370.0000.0240.0910.0560.0050.0120.0000.0000.5570.2970.5020.4980.0910.4750.1940.4340.0490.2190.1590.2510.1630.0110.0000.067
HourCounters Average GridOk Avg. [h]0.2680.0570.0000.0000.0000.0000.0000.0320.0000.0130.0000.0140.0410.0550.0170.0000.0080.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0070.0220.0000.0350.0000.0000.0010.0000.0230.0210.0130.0040.0000.0020.0030.0140.0230.0000.0400.0270.0100.0100.0180.0300.0000.0000.0000.0040.0000.0000.0220.0120.0000.0030.1570.4090.0060.0131.0000.5030.1950.6220.2880.0280.0000.0000.0080.0570.0570.0410.0080.0000.0090.0090.0160.0230.0000.0080.0000.0210.0000.0180.0070.0000.000
HourCounters Average GridOn Avg. [h]0.5040.4520.0000.0000.0000.0000.0000.0490.0110.0030.0230.0000.0280.0630.0130.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0260.0000.0030.0000.0000.0000.0000.0000.0000.0060.0060.0000.0060.0060.0000.0070.0280.0140.0000.0140.0200.0220.0200.0000.0000.0000.0000.0000.0030.0060.0000.0000.0000.1350.2230.0000.0000.5031.0000.0930.3660.1530.0770.0000.0000.0000.4520.4520.0390.0000.0050.0120.0000.0140.0070.0050.0100.0000.0200.0000.0000.0190.0000.000
HourCounters Average Run Avg. [h]0.0670.0180.0000.0000.0370.0000.0000.0000.0000.1870.1140.1680.1430.0000.0350.0000.0000.0100.0000.0280.0370.0470.0470.0660.0390.0760.0140.0100.0000.0000.0000.0000.1780.1090.1360.1450.0000.0000.0260.0960.2000.1910.1930.0000.1290.1330.0990.1200.1920.1150.1010.2230.1800.1070.1250.1040.0000.0000.0000.0210.0000.0080.0170.0000.0030.0030.9340.7090.2700.0370.1950.0931.0000.1350.5650.1060.0360.0290.0000.0180.0180.2590.1790.0140.2250.1290.0040.2050.1330.0050.1850.0960.1170.1210.0260.0000.000
HourCounters Average ServiceOn Avg. [h]0.2610.3230.0000.0000.0000.0000.0000.0250.0110.0110.0000.0040.0280.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0130.0010.0240.0000.0000.0000.0000.0180.0160.0170.0060.0000.0160.0000.0170.0170.0010.0300.0230.0060.0150.0000.0100.0000.0000.0000.0000.0000.0030.0120.0050.0000.0060.1980.2760.0080.0000.6220.3660.1351.0000.2210.0260.0000.0000.0000.3230.3230.0140.0100.0000.0120.0000.0000.0180.0000.0100.0000.0150.0000.0060.0000.0000.000
HourCounters Average TurbineOk Avg. [h]0.0500.0320.0070.0000.0000.0000.0000.0000.0080.1030.0440.0890.0810.0120.0000.0000.0000.0010.0000.0000.0000.0140.0090.0330.0050.0510.0180.0130.0000.0000.0000.0000.0900.0320.0750.0870.0000.0000.0000.0340.0360.0380.0300.0000.0000.0150.0040.0160.0310.0140.0370.1230.0940.0610.0780.0570.0000.0000.0000.0000.0040.0000.0240.0030.0020.0000.5300.1260.1330.0240.2880.1530.5650.2211.0000.0000.0000.0090.0080.0320.0320.1380.0160.0130.1190.0650.0090.0410.0700.0000.0890.0370.0640.0660.0000.0000.000
HourCounters Average WindOk Avg. [h]0.0490.0310.0080.0000.0000.0410.0560.0550.0150.0790.1570.0950.0530.0070.0050.0000.0000.0110.0300.0330.0300.0000.0040.0220.0040.0000.0000.0120.0190.0150.0110.0140.0160.0320.1020.0390.0000.0000.0310.1370.1600.1550.1410.0110.1530.0490.0850.0660.1570.0620.0860.0770.0850.0830.0600.0070.0060.0000.0000.0340.0360.0150.0150.0040.0160.0000.1070.1400.0120.0910.0280.0770.1060.0260.0001.0000.0240.0240.0130.0310.0310.1690.0190.1270.1330.0370.0770.1610.0360.0110.0200.0080.1020.0000.0000.0000.010
HourCounters Average Yaw Avg. [h]0.0000.0000.0050.0260.0110.0050.0140.0000.0560.0740.0380.0440.0910.0000.0060.0000.0080.0190.0090.0000.0070.0030.0000.0130.0050.0210.0110.0000.0000.0090.0000.0160.0350.0320.0250.0920.0140.0060.0070.0630.0530.0580.0640.0000.0490.0360.0730.0870.0640.0310.0990.0870.0620.1580.1830.0960.0000.0000.0000.0110.0160.0090.0130.0140.0220.0100.0310.0220.0100.0560.0000.0000.0360.0000.0000.0241.0000.0090.0200.0000.0000.0720.0170.0600.0750.0110.0770.0620.0370.0070.0310.0430.0240.0640.0000.0000.000
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0030.0000.0000.0000.0000.0050.0000.0200.0130.0150.0340.0120.0270.0370.0210.0000.0000.0000.0050.0000.0050.0000.0090.0000.0130.0270.0120.0080.0000.0000.0000.0000.0000.0360.0000.0000.0090.0270.0000.0000.0000.0000.0000.0350.0000.0000.0090.0000.0060.0000.0130.0000.0100.0000.0260.0230.0060.0050.0000.0000.0290.0000.0090.0240.0091.0000.0160.0000.0000.0000.0240.0000.0000.0450.0110.0150.0250.0030.0000.0000.0110.0260.0200.0000.000
Nacelle Temp. Avg. [°C]0.0000.0000.1030.0110.0130.0120.0000.0000.0300.0160.0250.0110.0160.0000.0150.0530.0000.0840.0340.0160.0160.0000.0100.0140.0240.0390.0140.0210.0430.0060.0260.0170.0210.0310.0000.0310.0430.0300.0080.0260.0210.0360.0320.0020.0260.0160.0310.0130.0270.0240.0280.0110.0250.0130.0080.0000.0020.0110.0130.0160.0270.0250.0320.0350.0310.0330.0000.0000.0130.0120.0080.0000.0000.0000.0080.0130.0200.0161.0000.0000.0000.0210.0000.0130.0340.0250.0130.0260.0000.0000.0220.0230.0000.0310.0520.0000.000
Power factor set point0.2730.8750.0000.0000.0050.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0010.0180.0000.0220.0000.0000.0000.0180.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0600.0240.0000.0000.0570.4520.0180.3230.0320.0310.0000.0000.0001.0000.8750.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0100.0000.0000.0170.0000.000
Power factor set point source0.2730.8750.0000.0000.0050.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0010.0180.0000.0220.0000.0000.0000.0180.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0600.0240.0000.0000.0570.4520.0180.3230.0320.0310.0000.0000.0000.8751.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0100.0000.0000.0170.0000.000
Production LatestAverage Active Power Gen 0 Avg. [W]0.0230.0000.0210.0250.0750.0270.0300.0460.0240.3120.1980.3900.2690.0050.0300.0000.0230.0080.0180.0410.1000.0290.1070.1130.0330.0710.0160.0230.0080.0100.0150.0120.2670.1780.3260.2490.0070.0030.0290.5230.2490.2310.2550.0000.1760.1540.1730.1720.2990.1900.1740.2440.5600.3250.3150.2930.0130.0150.0100.0300.0240.0310.0120.0020.0000.0000.2660.2070.0670.5570.0410.0390.2590.0140.1380.1690.0720.0000.0210.0000.0001.0000.0350.1610.7360.0000.3610.3460.4110.0550.2740.1540.2590.2070.0350.0000.084
Production LatestAverage Active Power Gen 1 Avg. [W]0.0080.0000.0090.0030.0000.0920.0570.0470.0000.1110.0000.1670.1320.0120.0270.0040.0240.0000.0070.0580.0400.0400.0750.0380.0240.0080.0000.0110.0180.0020.0000.0000.0530.0160.1400.0250.0240.0170.0130.0000.2200.2050.2040.0000.2820.0960.1180.1200.2800.0860.0990.1450.1720.1200.0830.1780.0150.0050.0260.0050.0190.0110.0090.0420.0510.0730.1790.2090.5940.2970.0080.0000.1790.0100.0160.0190.0170.0240.0000.0000.0000.0351.0000.0000.0260.1730.0790.3450.1350.0040.0580.0060.1180.0330.0000.0000.007
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0000.0060.0070.0050.1190.0540.0730.0250.2390.1080.2930.2410.0000.0480.0000.0100.0070.0090.0010.0000.0120.0050.0150.0000.0100.0160.0310.0130.0130.0020.0000.0960.1610.1310.1390.0140.0220.0390.1940.3300.3270.3670.0060.4260.2360.2830.2610.4470.2550.2640.2740.2610.1990.1070.1890.0000.0000.0000.0140.0120.0050.0070.0050.0000.0000.0000.0000.3360.5020.0000.0050.0140.0000.0130.1270.0600.0000.0130.0000.0000.1610.0001.0000.1360.0660.2750.4650.1760.0000.1100.1250.1060.1070.0000.0040.002
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0100.0000.0180.0210.0920.0340.0300.0500.0140.3010.2130.3530.2630.0090.0290.0000.0250.0130.0150.0360.0910.0310.1050.1100.0310.0710.0160.0250.0170.0140.0220.0140.2740.2060.2850.2530.0110.0000.0270.4960.2530.2770.2890.0000.1570.1590.1680.1880.2360.2270.1700.2330.6540.3420.3150.2910.0030.0040.0000.0340.0260.0340.0220.0000.0000.0000.2360.1700.0580.4980.0090.0120.2250.0120.1190.1330.0750.0000.0340.0000.0000.7360.0260.1361.0000.0010.3440.2260.5250.0680.2790.1720.2210.2100.0420.0000.110
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0000.0050.0000.0000.0070.0260.0000.1210.0000.2270.1870.0000.0060.0130.0080.0000.0190.0050.0020.0370.0000.0070.0160.0080.0000.0000.0170.0290.0280.0300.0250.0000.0240.0160.0110.0170.0060.0440.0100.0000.0040.0000.0220.0410.0050.0740.0140.0070.0000.1230.2450.2330.0970.2040.0000.0000.0000.0280.0230.0280.0100.0080.0070.0000.1280.0980.2650.0910.0090.0000.1290.0000.0650.0370.0110.0450.0250.0000.0000.0000.1730.0660.0011.0000.0810.0150.7170.0130.0090.0100.0130.0380.0000.0000.018
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0000.0050.0080.0240.0000.0130.0530.0350.2380.0540.4330.4550.0000.0220.0090.0070.0110.0060.0050.0220.0230.0220.0190.0060.0460.0060.0180.0060.0150.0120.0170.1050.1180.1980.2790.0170.0180.0000.3500.0640.0610.0810.0000.1230.1100.2410.1410.1110.0960.2050.1610.5150.3130.2580.4220.0000.0000.0000.0090.0180.0170.0000.0220.0220.0310.0000.0000.1870.4750.0160.0140.0040.0000.0090.0770.0770.0110.0130.0000.0000.3610.0790.2750.3440.0811.0000.1140.3940.1160.1100.0920.1450.2250.0090.0000.148
Production LatestAverage Total Active Power Avg. [W]0.0170.0000.0090.0090.0060.2140.0980.0740.0350.2000.1240.1860.1440.0000.0470.0000.0080.0040.0240.0840.0590.0620.0830.0420.0430.0310.0150.0390.0110.0180.0190.0220.1530.1290.1590.1520.0000.0150.0720.2090.6300.6010.6480.0070.6660.2950.3280.2890.8550.3400.3470.3380.1820.1110.1030.1170.0060.0000.0000.0440.0360.0330.0200.0120.0100.0000.1860.2070.0890.1940.0230.0070.2050.0180.0410.1610.0620.0150.0260.0000.0000.3460.3450.4650.2260.0150.1141.0000.1290.0070.1650.1050.1300.1400.0250.0060.009
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0070.0140.0490.0270.0280.0620.0020.2910.1230.4470.3310.0000.0060.0000.0110.0080.0030.0180.0390.0320.0630.0620.0220.0200.0080.0080.0000.0130.0080.0150.1580.1250.1820.1270.0000.0160.0000.2670.1440.1550.1650.0000.0950.1230.0920.1650.1380.1390.0970.1980.6830.4460.2960.3780.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.1380.1010.2550.4340.0000.0050.1330.0000.0700.0360.0370.0250.0000.0000.0000.4110.1350.1760.5250.7170.3940.1291.0000.0220.1460.1130.1360.1220.0170.0000.045
Reactive power generator 0,Total accumulated [var]0.0000.0240.0000.0000.0000.0000.0000.0000.0080.0260.0000.0460.0700.0000.0000.0000.0030.0000.0050.0020.0180.0000.0070.0110.0000.0000.0000.0000.0130.0030.0000.0020.0560.0170.0690.0840.0000.0000.0000.0430.0070.0080.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0500.0090.0420.0450.0000.0000.0000.0040.0000.0020.0000.0000.0090.0000.0000.0000.0000.0490.0080.0100.0050.0100.0000.0110.0070.0030.0000.0240.0240.0550.0040.0000.0680.0130.1160.0070.0221.0000.0560.0150.0530.0650.0000.0000.188
Rotor RPM Avg. [RPM]0.0000.0000.0170.0200.0640.1160.0420.0720.0230.2270.0900.2050.1630.0100.0180.0000.0180.0090.0230.0790.1240.1210.1540.1810.1230.0750.0410.0250.0200.0260.0210.0330.7280.3000.3710.4240.0290.0050.0050.1650.1570.1520.1650.0000.1560.1400.1450.1380.1570.1330.1110.1530.2040.1250.1360.1010.0000.0000.0000.0160.0240.0270.0100.0040.0000.0080.1730.1350.0890.2190.0000.0000.1850.0000.0890.0200.0310.0000.0220.0000.0000.2740.0580.1100.2790.0090.1100.1650.1460.0561.0000.2720.3360.3920.0200.0000.046
Rotor RPM Max. [RPM]0.0130.0100.0080.0290.0730.0640.0590.0360.0130.1760.2050.1060.1100.0060.0240.0000.0090.0040.0100.0470.0520.0640.0640.0940.0800.0870.0440.0220.0190.0060.0000.0000.3310.7300.1180.2400.0230.0000.0170.1010.1040.1010.1090.0000.1070.1400.1170.1450.0990.1420.0770.1170.1310.1050.0560.0720.0070.0000.0000.0200.0280.0340.0120.0000.0000.0000.0890.0880.0690.1590.0210.0200.0960.0150.0370.0080.0430.0000.0230.0100.0100.1540.0060.1250.1720.0100.0920.1050.1130.0150.2721.0000.1090.1860.0160.0000.017
Rotor RPM Min. [RPM]0.0110.0000.0170.0000.0330.0680.0240.1000.0020.1530.0410.2480.1560.0000.0130.0150.0000.0150.0300.0750.1040.0810.1290.1220.0840.0160.0180.0190.0160.0250.0380.0380.3410.1060.7550.2270.0250.0020.0180.1470.0930.0960.0950.0000.0950.0600.1360.0530.1180.0430.1390.0780.1990.1390.1720.1000.0080.0040.0000.0290.0350.0300.0070.0000.0000.0000.1080.0660.1420.2510.0000.0000.1170.0000.0640.1020.0240.0110.0000.0000.0000.2590.1180.1060.2210.0130.1450.1300.1360.0530.3360.1091.0000.1830.0000.0000.044
Rotor RPM StdDev [RPM]0.0160.0000.0070.0150.0350.0340.0070.0500.0690.1540.0610.1790.2930.0040.0210.0060.0360.0190.0000.0580.0780.0820.0840.0740.0670.0890.0380.0330.0000.0160.0080.0030.3990.2030.2210.6690.0170.0100.0100.1950.1090.1110.1170.0000.1460.1550.2090.1800.1360.1520.1670.2120.1490.0920.0910.1920.0000.0000.0110.0120.0160.0190.0000.0000.0000.0000.1180.0780.0160.1630.0180.0000.1210.0060.0660.0000.0640.0260.0310.0000.0000.2070.0330.1070.2100.0380.2250.1400.1220.0650.3920.1860.1831.0000.0250.0000.045
Spinner Temp. Avg. [°C]0.0130.0170.0420.0000.0130.0000.0000.0050.0000.0000.0070.0060.0050.0050.0650.0110.0070.0320.0000.0040.0200.0000.0140.0180.0080.0220.0000.0000.0160.0060.0000.0000.0160.0280.0140.0130.0000.0000.0000.0260.0180.0260.0280.0000.0120.0330.0190.0000.0200.0400.0190.0000.0200.0000.0110.0020.0000.0000.0000.0080.0000.0000.0000.0070.0090.0010.0230.0290.0000.0110.0070.0190.0260.0000.0000.0000.0000.0200.0520.0170.0170.0350.0000.0000.0420.0000.0090.0250.0170.0000.0200.0160.0000.0251.0000.0000.003
Total Active power [W]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0001.0000.000
Total reactive power [var]0.0000.0000.0000.0000.0130.0000.0000.0000.0080.0190.0000.0400.0610.0000.0000.0220.0080.0000.0040.0030.0140.0060.0000.0000.0000.0000.0000.0000.0110.0070.0060.0000.0500.0110.0550.0560.0000.0070.0000.0930.0090.0100.0100.0000.0070.0060.0210.0090.0090.0000.0000.0000.0670.0270.0290.0680.0000.0000.0000.0050.0040.0000.0000.0000.0000.0000.0000.0000.0080.0670.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0840.0070.0020.1100.0180.1480.0090.0450.1880.0460.0170.0440.0450.0030.0001.000

Missing values

2025-05-14T19:44:21.819663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T19:44:22.548637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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72020-01-01 01:10:0000000100011000000000100000000010010000000000000000000100000000000000000000111011001001000000000010000000000000000000000000000000
82020-01-01 01:20:0000100000110000000000101001000000010000000000000000000000000000000000000000111001000000001000000000000000000000000000000000000000
92020-01-01 01:30:0000101001100000100001101011000000010000000000000000000000000000000000000000011001010000001000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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